Name
Abstract | ||
|---|---|---|
We describe a new variational lower-bound on the minimum energy configuration of a planar binary Markov Random Field (MRF). Our method is based on adding auxiliary nodes to every face of a planar embedding of the graph in order to capture the effect of unary potentials. A ground state of the resulting approximation can be computed efficiently by reduction to minimum-weight perfect matching. We show that optimization of variational parameters achieves the same lower-bound as dual-decomposition into the set of all cycles of the original graph. We demonstrate that our variational optimization converges quickly and provides high-quality solutions to hard combinatorial problems 10-100x faster than competing algorithms that optimize the same bound. |
Year | Venue | Keywords |
|---|---|---|
2011 | Clinical Orthopaedics and Related Research | ground state,data structure,lower bound |
Field | DocType | Volume |
Graph,Mathematical optimization,Ground state,Unary operation,Markov random field,Planar straight-line graph,Matching (graph theory),Planar,Artificial intelligence,Machine learning,Mathematics,Binary number | Journal | abs/1104.1 |
Citations | PageRank | References |
3 | 0.39 | 18 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Julian Yarkony | 1 | 76 | 9.20 |
| Alexander T. Ihler | 2 | 1377 | 112.01 |
| Charless C Fowlkes | 3 | 7294 | 384.48 |